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Peng Shi

Researcher at University of Adelaide

Publications -  1601
Citations -  80441

Peng Shi is an academic researcher from University of Adelaide. The author has contributed to research in topics: Control theory & Nonlinear system. The author has an hindex of 137, co-authored 1371 publications receiving 65195 citations. Previous affiliations of Peng Shi include Harbin Engineering University & Harbin University of Science and Technology.

Papers
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Sliding Mode Control for Markov Jump Systems With Delays via Asynchronous Approach

TL;DR: In this paper, a sliding mode control (SMC) is considered for a class of nonlinear continuous-time Markov jump systems (MJSs) with uncertainties and time delay, where the controller gain may jump asynchronously with original MJSs.
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Structural Origins of Elastic and 2D Plastic Flexibility of Molecular Crystals Investigated with Two Polymorphs of Conformationally Rigid Coumarin

TL;DR: In this article, the structural origins of diverse mechanical behaviors of organic crystals are investigated for designing functional materials for a number of technological applications, including artificial intelligence, medical, and robotics.
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Robust Finite-Time H ∞ Control for Nonlinear Jump Systems via Neural Networks

TL;DR: A neural network-based robust finite-time H∞ control design approach for a class of nonlinear Markov jump systems (MJSs) and results are given to illustrate the effectiveness of the developed theoretic results.
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Fuzzy model-based robust H∞ filtering for a class of nonlinear nonhomogeneous Markov jump systems

TL;DR: This paper studies the problem of robust fuzzy H"~ filtering for a class of uncertain nonlinear discrete-time Markov jump systems with nonhomogeneous jump transition probabilities and proposes Lyapunov function approach and mode-dependent and variation-dependent fuzzy filter.
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H∞ filtering for a class of switched linear parameter varying systems

TL;DR: A mode-dependent full-order parameterised filter is designed and the corresponding existence conditions of such filters are derived via LMI formulation such that the resulting filter error system is exponentially stable and has a guaranteed H ∞ performance.